Modern day hearing aids, when employing different hearing programs, permit their adaptation to varying acoustic environments or scenes. The hearing program can be selected either via a remote control a by means of a selector switch on the hearing device itself. For many users, however, having to switch program settings is a nuisance, or difficult, or even impossible. Nor it is always easy even for experienced wearers of hearing devices to determine at what point in time which program is most comfortable and offers optimal speech discrimination. An automatic recognition of the acoustic scene and corresponding automatic switching of the hearing program settings in the hearing device is therefore desirable.
There exist several different approaches to the automatic classification of acoustic scenes or of an acoustic input signal, respectively. All of the methods concerned involve the extraction of different features from the input signal, which may be derived from one or several microphones in the hearing device. Based on these features, a pattern recognition device employing a particular algorithm makes the determination as to the attribution of the analyzed signal to a specific acoustic scene. These various existing methods differ from one another both in terms of the features on the basis of which they define the acoustic scene (signal analysis) and with regard to the pattern recognition device, which serves to classify these features (signal identification).
From the publication of the international patent application having the publication file No. WO 01/20965 a method and a device for identifying an acoustic scene are known. Described is a single-stage process in which an acoustic input signal is processed in a feature extraction unit and, afterwards, in a classification unit, in which the extracted features are classified to generate class information. Good results are obtained by this known teaching in particular if audio-based features are also extracted. An improvement is desirable particularly in the field of hearing devices, since in this application field the classification of acoustic scenes must be very accurate. At the same time, the occurrence of several very broad sound classes, as e.g. music or noise, cause greater difficulties. It corresponds to the nature of these sound classes that they are very general and broad, i.e. their occurrence may be in manifold manner. The sound class “noised”, for examples comprises very different sounds as e.g. background noise resulting from discussions, train station noise, hair dryer noise, and the sound class “music” comprises for example pop music, classic music, single instruments, singing, etc.
Especially because of the very general nature of these sound classes, it is very difficult to obtain a good recognition rate with the aid of the known processing methods in a feature extraction unit and a following classification unit. In fact, the robustness of the recognition system can be improved by the selection of features as has been described in WO 01/20965 for the first time, namely by using auditory-based features. Nevertheless, it is very difficult to separate between different general sound classes in a clear and doubtless manner, because of the high variance of these general sound classes.
It is therefore an object of this invention to introduce a method for identifying an acoustic scene, which is more reliable and more precise compared to prior art methods.